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一种基于风险的方法来模拟网络购物对购物间隔时长的影响。

A hazard-based approach to modelling the effects of online shopping on intershopping duration.

作者信息

Suel Esra, Daina Nicolò, Polak John W

机构信息

Centre for Transport Studies, Imperial College London, Exhibition Road, London, SW7 2AZ UK.

出版信息

Transportation (Amst). 2018;45(2):415-428. doi: 10.1007/s11116-017-9838-3. Epub 2017 Nov 21.

Abstract

Despite growing prevalence of online shopping, its impacts on mobility are poorly understood. This partially results from the lack of sufficiently detailed data. In this paper we address this gap using consumer panel data, a new dataset for this context. We analyse one year long longitudinal grocery shopping purchase data from London shoppers to investigate the effects of online shopping on overall shopping activity patterns and personal trips. We characterise the temporal structure of shopping demand by means of the duration between shopping episodes using hazard-based duration models. These models have been used to study inter-shopping spells for traditional shopping in the literature, however effects of online shopping were not considered. Here, we differentiate between shopping events and shopping trips. The former refers to all types of shopping activity including both online and in-store, while the latter is restricted to physical shopping trips. Separate models were estimated for each and results suggest potential substitution effects between online and in-store in the context of grocery shopping. We find that having shopped online since the last shopping trip significantly reduces the likelihood of a physical shopping trip. We do not observe the same effect for inter-event durations. Hence, shopping online does not have a significant effect on overall shopping activity frequency, yet affects shopping trip rates. This is a key finding and suggests potential substitution between online shopping and physical trips to the store. Additional insights on which factors, including basket size and demographics, affect inter-shopping durations are also drawn.

摘要

尽管网上购物的普及率不断提高,但其对出行的影响却鲜为人知。部分原因是缺乏足够详细的数据。在本文中,我们使用消费者面板数据来填补这一空白,这是针对此背景的一个新数据集。我们分析了伦敦购物者长达一年的纵向食品杂货购买数据,以研究网上购物对整体购物活动模式和个人出行的影响。我们使用基于风险的持续时间模型,通过购物时段之间的持续时间来刻画购物需求的时间结构。这些模型在文献中已被用于研究传统购物的购物间隔期,然而并未考虑网上购物的影响。在这里,我们区分购物事件和购物行程。前者指包括网上购物和实体店购物在内的所有类型的购物活动,而后者仅限于实体购物行程。我们为每种情况分别估计了模型,结果表明在食品杂货购物的背景下,网上购物和实体店购物之间存在潜在的替代效应。我们发现,自上次购物行程以来进行过网上购物,会显著降低进行实体购物行程的可能性。对于事件间隔期,我们没有观察到同样的效果。因此,网上购物对整体购物活动频率没有显著影响,但会影响购物行程率。这是一个关键发现,表明网上购物和前往商店的实体行程之间存在潜在替代关系。我们还得出了关于哪些因素(包括购物篮大小和人口统计学因素)会影响购物间隔期的其他见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a25a/6560787/7e41fd9ac917/11116_2017_9838_Fig1_HTML.jpg

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